Stitching and Geometric Modeling Approach Based on Multi-Slice Satellite Images

Time delay and integration (TDI) charge-coupled device (CCD) is an image sensor for capturing images of moving objects at low light levels. This study examines the model construction of stitched TDI CCD original multi-slice images. The traditional approaches, for example, include the image-space-oriented algorithm and the object-space-oriented algorithm. The former indicates concise principles and high efficiency, whereas the panoramic stitching images lack the clear geometric relationships generated from the image-space-oriented algorithm. Similarly, even though the object-space-oriented algorithm generates an image with a clear geometric relationship, it is time-consuming due to the complicated and intensive computational demands. In this study, we developed a multi-slice satellite images stitching and geometric model construction method. The method consists of three major steps. First, the high-precision reference data assist in block adjustment and obtain the original slice image bias-corrected RFM to perform multi-slice image block adjustment. The second process generates the panoramic stitching image by establishing the image coordinate conversion relationship from the panoramic stitching image to the original multi-slice images. The final step is dividing the panoramic stitching image uniformly into image grids and employing the established image coordinate conversion relationship and the original multi-slice image bias-corrected RFM to generate a virtual control grid to construct the panoramic stitching image RFM. To evaluate the performance, we conducted experiments using the Tianhui-1(TH-1) high-resolution image and the Ziyuan-3(ZY-3) triple liner-array image data. The experimental results show that, compared with the object-space-oriented algorithm, the stitching accuracy loss of the generated panoramic stitching image was only 0.2 pixels and that the mean value was 0.799798 pixels, achieving the sub-pixel stitching requirements. Compared with the object-space-oriented algorithm, the RFM positioning difference of the panoramic stitching image was within 0.3 m, which achieves equal positioning accuracy.

Investigation of Non-Destructive Testing in Inner Cavity with Ant-Nest Structure Based on Positron Annihilation

The existing testing method could not accurately detect the defects in inner cavity with ant-nest structure in a part. The reasons are as follows: the shape of inner cavity is irregular, the distribution of wall thickness is uneven and the material composition is complex etc. A new testing method is proposed based on positron annihilation in this paper. The radionuclide solution is injected in inner cavity of the part and then produces positrons which would annihilate within 2 nanoseconds in the polylactide (PLA) material. The information of inner cavity is reflected by counting the γ photons produced by positron annihilation. The maximum likelihood estimation model (MLEM) with average compensation is established according to the detected γ photons. A 2D slice image sequence is obtained by order subset expectation maximization (OSEM) algorithm which solves the MLEM. The targets such as defects in the 2D slice image need to be enhanced by OTSU algorithm. A 3D image is reconstructed by the enhanced 2D slice image sequence which is used to the detection and location of the defects in inner cavity. Two experiments under different environment are conducted which aim at different ant-nest structure parts. The parts are made of different material and made by different manufacture process. A good testing result of the parts with complex shaped inner cavity could be obtained. The results would not change with the change of external temperature or magnetic field and the testing precision can reach to millimeter level.